Graph-based Knowledge Representation

Graph-based Knowledge Representation PDF

Author: Michel Chein

Publisher: Springer Science & Business Media

Published: 2008-10-20

Total Pages: 428

ISBN-13: 1848002866

DOWNLOAD EBOOK →

This book provides a de?nition and study of a knowledge representation and r- soning formalism stemming from conceptual graphs, while focusing on the com- tational properties of this formalism. Knowledge can be symbolically represented in many ways. The knowledge representation and reasoning formalism presented here is a graph formalism – knowledge is represented by labeled graphs, in the graph theory sense, and r- soning mechanisms are based on graph operations, with graph homomorphism at the core. This formalism can thus be considered as related to semantic networks. Since their conception, semantic networks have faded out several times, but have always returned to the limelight. They faded mainly due to a lack of formal semantics and the limited reasoning tools proposed. They have, however, always rebounded - cause labeled graphs, schemas and drawings provide an intuitive and easily und- standable support to represent knowledge. This formalism has the visual qualities of any graphic model, and it is logically founded. This is a key feature because logics has been the foundation for knowledge representation and reasoning for millennia. The authors also focus substantially on computational facets of the presented formalism as they are interested in knowledge representation and reasoning formalisms upon which knowledge-based systems can be built to solve real problems. Since object structures are graphs, naturally graph homomorphism is the key underlying notion and, from a computational viewpoint, this moors calculus to combinatorics and to computer science domains in which the algorithmicqualitiesofgraphshavelongbeenstudied,asindatabasesandconstraint networks.

Graph-based Knowledge Representation

Graph-based Knowledge Representation PDF

Author: Michel Chein

Publisher: Springer

Published: 2008-10-21

Total Pages: 428

ISBN-13: 9781848002852

DOWNLOAD EBOOK →

This book provides a de?nition and study of a knowledge representation and r- soning formalism stemming from conceptual graphs, while focusing on the com- tational properties of this formalism. Knowledge can be symbolically represented in many ways. The knowledge representation and reasoning formalism presented here is a graph formalism – knowledge is represented by labeled graphs, in the graph theory sense, and r- soning mechanisms are based on graph operations, with graph homomorphism at the core. This formalism can thus be considered as related to semantic networks. Since their conception, semantic networks have faded out several times, but have always returned to the limelight. They faded mainly due to a lack of formal semantics and the limited reasoning tools proposed. They have, however, always rebounded - cause labeled graphs, schemas and drawings provide an intuitive and easily und- standable support to represent knowledge. This formalism has the visual qualities of any graphic model, and it is logically founded. This is a key feature because logics has been the foundation for knowledge representation and reasoning for millennia. The authors also focus substantially on computational facets of the presented formalism as they are interested in knowledge representation and reasoning formalisms upon which knowledge-based systems can be built to solve real problems. Since object structures are graphs, naturally graph homomorphism is the key underlying notion and, from a computational viewpoint, this moors calculus to combinatorics and to computer science domains in which the algorithmicqualitiesofgraphshavelongbeenstudied,asindatabasesandconstraint networks.

Conceptual Graphs for Knowledge Representation

Conceptual Graphs for Knowledge Representation PDF

Author: Guy W. Mineau

Publisher: Springer Science & Business Media

Published: 1993-07-14

Total Pages: 470

ISBN-13: 9783540569794

DOWNLOAD EBOOK →

Artificial Intelligence and cognitive science are the two fields devoted to the study and development of knowledge-based systems (KBS). Over the past 25years, researchers have proposed several approaches for modeling knowledge in KBS, including several kinds of formalism such as semantic networks, frames, and logics. In the early 1980s, J.F. Sowa introduced the conceptual graph (CG) theory which provides a knowledge representation framework consisting of a form of logic with a graph notationand integrating several features from semantic net and frame representations. Since that time, several research teams over the world have been working on the application and extension of CG theory in various domains ranging from natural language processing to database modeling and machine learning. This volume contains selected papers fromthe international conference on Conceptual Structures held in the city of Quebec, Canada, August 4-7, 1993. The volume opens with invited papers by J.F. Sowa, B.R. Gaines, and J. Barwise.

Graph Structures for Knowledge Representation and Reasoning

Graph Structures for Knowledge Representation and Reasoning PDF

Author: Madalina Croitoru

Publisher: Springer

Published: 2014-01-21

Total Pages: 220

ISBN-13: 3319045342

DOWNLOAD EBOOK →

This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2013, held in Beijing, China, in August 2013, associated with IJCAI 2013, the 23rd International Joint Conference on Artificial Intelligence. The 12 revised full papers presented were carefully reviewed and selected for inclusion in the book. The papers feature current research involved in the development and application of graph-based knowledge representation formalisms and reasoning techniques. They address the following topics: representations of constraint satisfaction problems; formal concept analysis; conceptual graphs; and argumentation frameworks.

Reasoning and Unification over Conceptual Graphs

Reasoning and Unification over Conceptual Graphs PDF

Author: Dan Corbett

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 155

ISBN-13: 1461500877

DOWNLOAD EBOOK →

Reasoning and Unification over Conceptual Graphs is an exploration of automated reasoning and resolution in the expanding field of Conceptual Structures. Designed not only for computing scientists researching Conceptual Graphs, but also for anyone interested in exploring the design of knowledge bases, the book explores what are proving to be the fundamental methods for representing semantic relations in knowledge bases. While it provides the first comprehensive treatment of Conceptual Graph unification and reasoning, the book also addresses fundamental issues of graph matching, automated reasoning, knowledge bases, constraints, ontology and design. With a large number of examples, illustrations, and both formal and informal definitions and discussions, this book is excellent as a tutorial for the reader new to Conceptual Graphs, or as a reference book for a senior researcher in Artificial Intelligence, Knowledge Representation or Automated Reasoning.

Handbook of Knowledge Representation

Handbook of Knowledge Representation PDF

Author: Frank van Harmelen

Publisher: Elsevier

Published: 2008-01-08

Total Pages: 1034

ISBN-13: 9780080557021

DOWNLOAD EBOOK →

Handbook of Knowledge Representation describes the essential foundations of Knowledge Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. It includes a tutorial background and cutting-edge developments, as well as applications of Knowledge Representation in a variety of AI systems. This handbook is organized into three parts. Part I deals with general methods in Knowledge Representation and reasoning and covers such topics as classical logic in Knowledge Representation; satisfiability solvers; description logics; constraint programming; conceptual graphs; nonmonotonic reasoning; model-based problem solving; and Bayesian networks. Part II focuses on classes of knowledge and specialized representations, with chapters on temporal representation and reasoning; spatial and physical reasoning; reasoning about knowledge and belief; temporal action logics; and nonmonotonic causal logic. Part III discusses Knowledge Representation in applications such as question answering; the semantic web; automated planning; cognitive robotics; multi-agent systems; and knowledge engineering. This book is an essential resource for graduate students, researchers, and practitioners in knowledge representation and AI. * Make your computer smarter * Handle qualitative and uncertain information * Improve computational tractability to solve your problems easily

Graph-Based Representation and Reasoning

Graph-Based Representation and Reasoning PDF

Author: Nathalie Hernandez

Publisher: Springer

Published: 2014-07-17

Total Pages: 311

ISBN-13: 3319083899

DOWNLOAD EBOOK →

This book constitutes the proceedings of the 21st International Conference on Conceptual Structures, ICCS 2014, held in Iaşi, Romania, in July 2014. The 17 regular papers and 6 short papers presented in this volume were carefully reviewed and selected from 40 and 10 submissions, respectively. The topics covered are: conceptual structures, knowledge representation, reasoning, conceptual graphs, formal concept analysis, semantic Web, information integration, machine learning, data mining and information retrieval.

Graph Structures for Knowledge Representation and Reasoning

Graph Structures for Knowledge Representation and Reasoning PDF

Author: Madalina Croitoru

Publisher: Springer

Published: 2018-03-29

Total Pages: 139

ISBN-13: 3319781022

DOWNLOAD EBOOK →

This book constitutes the thoroughly refereed post-conference proceedings of the 5th International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2017, held in Melbourne, VIC, Australia, in August 2017, associated with IJCAI 2017, the 26th International Joint Conference on Artificial Intelligence. The 7 revised full papers presented were reviewed and selected from 9 submissions. The contributions address various issues for knowledge representation and reasoning and the common graph-theoretic background allows to bridge the gap between the different communities.